Classification and Discriminant Analysis: Difference between revisions
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:[[discrimprob]] - Discriminate probabilities for continuous predicted values. | :[[discrimprob]] - Discriminate probabilities for continuous predicted values. | ||
:[[plsdaroc]] - Calculate and display ROC curves for PLSDA model. | :[[plsdaroc]] - Calculate and display ROC curves for PLSDA model. | ||
:[[plsdthres]] - Bayesian threshold determination for PLS Discriminate Analysis. | |||
(Sub topic of [[Qualitative_Exploratory_Analysis_and_Classification|Qualitative Exploratory Analysis and Classification]]) | (Sub topic of [[Qualitative_Exploratory_Analysis_and_Classification|Qualitative Exploratory Analysis and Classification]]) | ||
Revision as of 14:21, 4 September 2008
These methods help separate samples into classes and develop models which can be used to predict which class a new sample belongs to.
- analysis - Graphical user interface for data analysis.
- simca - Soft Independent Method of Class Analogy.
- plsda - Partial least squares discriminant analysis.
- knn - K-nearest neighbor classifier.
Model Analysis and Calculation Utilities
- class2logical - Create a PLSDA logical block from class assignments.
- discrimprob - Discriminate probabilities for continuous predicted values.
- plsdaroc - Calculate and display ROC curves for PLSDA model.
- plsdthres - Bayesian threshold determination for PLS Discriminate Analysis.
(Sub topic of Qualitative Exploratory Analysis and Classification)